Data Infrastructure Engineer - Houzz

Job Title: Data Infrastructure Engineer
Job Location: Taiwan
Job Listing URL: https://jobs.lever.co/houzz/fbd2b081-a994-49bc-8f9d-8c779ccaa291
Job Description: About the Role

We are looking for a world-class engineer to join our data infrastructure team. Our mission is to drive stability, scalability and efficiency for the Houzz data ecosystem and build critical systems that provide insights to drive growth and delight our customers. The right candidate can architect, implement, and be an end-to-end owner across our suite of tools that includes data pipelines, event streaming, and data warehouse/data lake.
What You’ll Do
Build scalable and reliable data infrastructure that processes petabytes of data
Integrate with big data technologies and workflow management frameworks such as EMR, Hadoop, Spark, Flink, Kafka, Trino/Presto, and Airflow
Automate the process of infra operation such as EMR provisioning and autoscaling
Build tools and framework for data analysis
Create monitoring and alerting processes for the data infrastructure team
Own service operation in production, including participating in on-call rotation
Working in a small, collaborative team with data engineers, data scientists, designers and product managers build an amazing data experience
Promote best practices and improve the quality of the internal data products
At a Minimum, We’d Like You to Have
Proficiency in a common programming or scripting language (Python, Bash, Java, etc.)
Minimum of 3 years of industry experience building large-scale reliable data backends
Experience with big data technology and workflow management frameworks like Apache Flink, Airflow, Apache Spark, Hive, Kafka, Kinesis, etc
Good understanding of Linux and Kubernetes, with experience utilizing services from a major cloud provider such as AWS, Azure, or Google Cloud Platform
Excellent communication, interpersonal and cross-functional skills
A minimum of Bachelor’s degree in Computer Science or a related field
Ideally, You’ll Also Have
Extensive knowledge and experience with large-scale, distributed systems
Experience building analytics frameworks and tools with broad adoption
Experience maintaining and optimizing data warehouses or data lakes, including ensuring data availability, reliability and quality

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